Summer 2023
Cupertino, USA

Machine Learning Research Intern, Apple Inc.

Research work with Machine Learning Research (MLR) Group. Advised by Rin Metcalf and Barry Theobald. Hindsight PRIORs for Reward Learning from Human Preferences. (ICLR 2024)

Summer 2022
Cupertino, USA

Machine Learning Research Intern, Apple Inc.

Preference based Reinforcement Learning research with Machine Learning Research (MLR) group Advised by Rin Metcalf Barry Theobald. Symbol Guided Hindsight Priors for Reward Learning from Human Preferences at IROS RLCONFORM, NeurIPS HILL 2022.

Summer 2021
Santa Clara, USA

Deep Learning Software Engineering Intern, Intel Corporation

• First analysis of float32 ResNet50 architecture on Intel IceLake (ICX) machines.
• Proposed Several optimizations (in parallel computing) like shared processes, to achieve BFloat16 performance (as bench- marked on CooperLake machines) on an ICX cluster.
• Additionally, first to provide the Best Known method (an automated way) for working with ResNet50 on Intel Endevour Cluster.
• Parallely, first to work with Quantized ResNet Models to show discrepancy in Saliency Based explanations between original RN50 and Quantized RN50.

Summer 2018
Bangalore, India 

Software Engineering Intern, Samsung Semiconductor India Research

• Created DRAM Bank Simulator, (400 times faster) with enhanced Fault Classes.
• Novel Approach to Redundancy Analysis Algorithms through State Space Reduction schemes &  Beating RA through Monte Carlo Tree Search and Residual Networks.
• Awarded Best Intern Project at SSIR.

Summer 2017
Bangalore, India 

Software Engineering Intern, Samsung Semiconductor India Research

• Diagnosed issues with SSDs & Implemented SSD Simulator for Read/Write/Garbage Collection.
• Created an LSTM based Algorithm - Stream Selection for Smart Data Categorization (STRASDAC) to reduce write-wearing in SSDs and in turn further improve Garbage Collection.
• Reached Best Intern Project Finals at SSIR.

2024

• Hindsight PRIORs for Reward Learning from Human Preferences

  Mudit Verma, Katherine Metcalf

  ICLR 2024

  PaperPoster

• Theory of Mind abilities of Large Language Models in Human-Robot Interaction : An Illusion?

  Mudit Verma*, Siddhant Bhambri*, Subbarao Kambhampati

  HRI 2024

  Invited Talk : AGI Leap Summit 2024

  Paper

2023

• Trust-Aware Planning: Modeling Trust Evolution in Iterated Human-Robot Interaction.

  Zahra Zadehi, Mudit Verma, Sreedharan, Subbarao Kambhampati

  Human Robot Interaction (HRI)

  PaperPoster

• Methods and Mechanisms for Interactive Novelty Handling in Adversarial Environments.

  Tung Thai, Mudit Verma, Utkarsh Soni, Gopalakrishnan S., Shen M., Garg M., Kalani A.,, Vaidya N., Kambhampati S., Varshney N., Baral C., Sinapov J., Scheutz M.

  AAMAS Extended Abstract

  Paper

• Preference Proxies: Evaluating Large Language Models in capturing Human Preferences in Human-AI Tasks

  Mudit Verma*, Siddhant Bhambri*, Subbarao Kambhampati

  Theory of Mind Workshop, Many Facets of Preference Learning (Oral) Workshop at ICML 2023.

  PaperPoster

• Exploiting Action Distances for Reward Learning from Human Preferences.

  Mudit Verma*, Siddhant Bhambri*, Subbarao Kambhampati

  In Many Facets of Preference Learning Workshop at ICML 2023.

  PaperSlides

• Data Driven Reward Initialization for Preference based Reinforcement Learning

  Mudit Verma, Subbarao Kambhampati

  In AAAI R2HCAI 2023.

  PaperSlides

• Exploiting Unlabeled Data for Feedback Efficient Human Preference based Reinforcement Learning.

  Mudit Verma, Siddhant Bhambri, Subbarao Kambhampati

  In AAAI R2HCAI 2023.

  PaperSlides

2022

• Symbol Guided Hindsight Priors for Reward Learning from Human Preferences

  Mudit Verma and Katherine Metcalf

  NeurIPS HILL 2022

  IROS RLCONFORM 2022

  Paper

• Advice Conformance Verification by Reinforcement Learning agents for Human-in-the-Loop

  Mudit Verma, Ayush Kharkwal, Subbarao Kambhampati

  NeurIPS HILL 2022

  IROS RLCONFORM 2022

  Paper Video

• Towards customizable reinforcement learning agents: Enabling preference specification through online vocabulary expansion

  Utkarsh Soni, Sarath Sreedharan, Mudit Verma, Subbarao Kambhampati

  NeurIPS HILL 2022

  Paper

• Computing Policies That Account for the Effects of Human Uncertainty During Execution in Markov Decision Processes

  Sriram Gopalakrishnan, Mudit Verma, Subbarao Kambhampati

  ICAPS Workshop on Explainable AI Planning (XAIP) 2022

  Paper

• Bridging the Gap: Providing Post-Hoc Symbolic Explanations for Sequential Decision-Making Problems with Inscrutable Representations

  Sarath Sreedharan, Utkarsh Soni, Mudit Verma, Siddharth Srivastava and Subbarao Kambhampati

  ICLR 2022

  Paper Video

• Symbols as a Lingua Franca for Bridging Human-AI Chasm for Explainable and Advisable AI Systems.

  Subbarao Kambhampati, Sarath Sreedharan, Mudit Verma, Yantian Zha, Lin Guan

  In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI) Blue Sky Track

  Paper

• Modeling the interplay between human trust and monitoring

  Zahra Zahedi, Sarath Sreedharan, Mudit Verma and Subbarao Kambhampati

  HRI 2022 (Late breaking paper)

  Paper

2021

• Widening the Pipeline in Human-Guided Reinforcement Learning with Explanation and Context-Aware Data Augmentation.

  Lin Guan, Mudit Verma, Sihang Guo, Ruohan Zhang, Subbarao Kambhampati

  In Advances in Neural Information Processing Systems. (NeurIPS) Spotlight

  Paper

• Trust-Aware Planning: Modeling Trust Evolution in Longitudinal Human-Robot Interaction

  Zahra Zadehi, Mudit Verma, Sarath Sreedharan, Subbarao Kambhampati

  In ICAPS 2021 Workshop on Explainable AI Planning, Also in ICAPS 2021 Workshop on Planning and Robotics

  Paper

• Synthesizing Policies That Account For Human Execution Er- rors Caused By State Aliasing In Markov Decision Processes

  Sriram Gopalakrishnan, Mudit Verma, Subbarao Kambhampati

  In ICAPS 2021 Workshop on Explainable AI Planning.

  Paper

2020

• Bridging the Gap: Providing Post-Hoc Symbolic Explanations for Sequential Decision-Making Problems with Black Box Simulators

  Sarath Sreedharan, Utkarsh Soni, Mudit Verma, Siddharth Srivastava, Subbarao Kambhampati

  ICML Workshop on Human in the Loop Learning (HILL)

  PaperPoster

• Explanation Augmented Feedback in Human-in-the-Loop Reinforcement Learning

  Lin Guan*, Mudit Verma*, Sihang Guo, Ruohan Zhang, Subbarao Kambhampati

  NeurIPS Deep Reinforcement Learning Workshop (DRL)
  NeurIPS Workshop on Human And Model in the Loop Evaluation and Training Strategies (HAMLETS)

  Paper

• Explanation Augmented Feedback in Human-in-the-Loop Reinforcement Learning

  Lin Guan*, Mudit Verma*, Subbarao Kambhampati

  ICML Workshop on Human in the Loop Learning (HILL)

  PaperPoster

• Fine-grained Language Identification with MultilingualCapsNetModel.

  Mudit Verma, Arun Balaji Buduru

  IEEE International Conference on Multimedia Big Data (BigMM)

  PaperSlides

2019

• A Novel Framework for Neural Architecture Search in the Hill Climbing Domain.

  Mudit Verma, Pradyumna Sinha, Karan Goyal, Apoorva Verma, Seba Susan

  IEEE Second International Conference on Artificial Intelligence and Knowledge Engineering (AIKE)

  Paper

• Making Smart Homes Smarter: Optimizing Energy Consumption with Human in the Loop

  Mudit Verma, Siddhant Bhambri, Saurabh Gupta, Arun Balaji Buduru

  Paper